The importance of enhancing the sustainability of buildings has been sharply growing over the last few years. One of the most significant aspects in this regard is social sustainability, as it encompasses the well-bei...
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The λDat calculus brings together the power of functional and declarative logic programming in one language. In λDat, Datalog constraints are first-class values that can be constructed, passed around as arguments, r...
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Answer Set programming is an automated reasoning technology that has become a prime candidate for solving knowledge-intense search and optimization problems. One of the main reasons of its success is the availability ...
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Answer Set programming is an automated reasoning technology that has become a prime candidate for solving knowledge-intense search and optimization problems. One of the main reasons of its success is the availability of highly effective solvers that can go toe-to-toe with Satisfiability Solvers while dealing with a high-level human understandable language. Epistemic logic programs are an extension of Answer Set programming with subjective literals that allow to succinctly represent several problems that cannot be represented using the standard language of Answer Set programming. eclingo is a solver developed to solve problems described in the language of Epistemic logic Programs. This research aims to enhance the efficiency of such solver. The focus of the research will be aimed at the use of the metaprogramming capabilities of Answer Set programming solver clingo. This will allow us to enhance the solver with new inference rules expressed in the Answer Set programming language. This will reduce the search space and, in principle, improve solver performance.
Communicating Datalog Programs (CDPs) are a distributed computing model grounded on logic programming, where networks of nodes perform Datalog-like computations, leveraging also on information coming from incoming mes...
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The promise of automation of legal reasoning is developing technology that reduces human time required for legal tasks or that improves human performance on such tasks. In order to do so, different methods and systems...
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The promise of automation of legal reasoning is developing technology that reduces human time required for legal tasks or that improves human performance on such tasks. In order to do so, different methods and systems based on logic programming were developed. However, in order to apply such methods on legal data, it is necessary to provide an interface between human users and the legal reasoning system, and the most natural interface in the legal domain is natural language, in particular, written text. In order to perform reasoning in written text using logic programming methods, it is then necessary to map expressions in text to atoms and predicates in the formal language, a task referred generally as information extraction. In this work, we propose a new dataset for the task of information extraction, in particular event extraction, in court decisions, focusing on contracts. Our dataset captures contractual relations and events that affect them in some way, such as negotiations preceding a (possible) contract, the execution of a contract, or its termination. We conducted text annotation with law students and graduates, resulting in a dataset with 207 documents, 3934 sentences, 4440 entities, and 1794 events. We describe here this resource, the annotation process, its evaluation with inter-annotator agreement metrics, and discuss challenges during the development of this resource and for the future. 2023 Copyright for this paper by its authors.
We present an approach to non-deterministic planning under full observability via Answer Set programming. The technique can synthesise compact policies, handle both fair and unfair actions simultaneously, and readily ...
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Complex Event Recognition (CER) systems detect event occurrences in streaming input using predefined event patterns. Techniques that learn event patterns from data are highly desirable in CER. Since such patterns are ...
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Predictive maintenance plays a key role in the core business of the industry due to its potential in reducing unexpected machine downtime and related cost. To avoid such issues, it is crucial to devise artificial inte...
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It is now widely acknowledged that working in marketable banking (MB) can be a major source of stress. Meeting overly ambitious commercial targets or adapting to changes in the industry can often result in stressful s...
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